In this day and age of the information explosion with abundant information, people's interests have become diverse. Consequently, it is getting more and more difficult to win the hears and minds of users with conventional and uniform techniques for presenting information. Thus required today is a technique to present personalized information; that is, casually conveyed information of the users' potential interests.
For example, the number of channels for a TV as a display device is rapidly increasing along with the digitalization of the recent TV broadcasting. So is the number of content items distributed via the Internet. As a result, a user can select a content item from among a large number of content items. However, it is very difficult for the user himself or herself to select his or her favorite content item from among a large number of content items. To overcome the difficulty, actively studied is a system to recommend programs which suit the user's interests.
In order to present content items which suit the interests of the user, content providers need to understand how much the user is interested in each of the content items that he or she views on a regular basis. In other words, the content providers need to estimate a degree of interest of the user in a viewed video.
Patent Literature 1 describes one of conventional techniques to estimate a degree of interest. The technique in Patent Literature 1 involves checking a user's viewing status of a content item and eye movement to analyze his or her eye blink frequency, response time, saccade speed, saccade duration, and a positional deviation of his or her eye gaze. Then, using each of the analysis results as a computational element, the technique involves calculating a degree of interest of the viewer in the content item. Furthermore, based on the calculation result and another calculation result held in a data holding device, the technique involves calculating a degree of interest of the viewer in a specific content item.